Integrity refers to the correspondence of data with itself, at its creation. Data lacks integrity when it has been changed accidentally or tampered with. For example, a hacker might change driver license data resulting in arrests of innocent people.
Data integrity is concerned with the ‘correctness’ of the data. Data cannot be regarded as having integrity if it has been accidentally changed or tampered with.
Data that lacks integrity cannot be trusted but is hard to spot. Errors may be introduced into data in a variety of ways. They can be introduced when the person typing in the data misreads it off a source document or if a program or machine errors corrupt data. Some types of corruption can be caused by simple typing errors.
Validation and verification checks are performed on data to ensure its integrity.
Verification
When keying-in very large quantities of data it is normal for some errors to occur in copying from the hand-written source documents. Mistakes made when copying are known as transcription errors. It is also quite common for people to transpose characters, so that 69 would become 96, for example. To eliminate copying errors the data is re-typed by a second key-to-disk operator and any differences in the two sets of data are notified by the computer. Checking and correcting errors made when keying-in data from source documents onto disk or tape is known as verification.
Validation
Validation checks are intended to ensure that the data is suitable for the purpose for which it is being used, in particular that the data is:
Of the correct type (alphabetic, numeric etc.)
Within an acceptable numerical range
Complete
In the right format
Validation checks must be combined with verification checks to reduce the number of errors in data input and ensure the integrity (accuracy and completeness) of the data. Validation type checks examples:
6-digit STD code: acceptable 028373
rejected 0392Z5 (alphabetic character included)
car registration: acceptable ACE 3641
rejected 8CE 3641 (number instead of letter at the start) Validation range checks examples:
school students/pupils ages: 5<=age<=19
examination percentages: 0<=marks<=100
Tasks:
Find a news item about data integrity or a data error problem. Briefly describe the scenario and discuss possible solutions.
Find the 1998 Data Protection Act. What duties does it impose on those who hold personal data? Save a copy of the main principles of the act for your notes.
Baase, Sara. A Gift of Fire. pg.136-142
Beekman, George. Computer Confluence seventh edition. Chapter 7: Database Applications and Privacy Implications
Integrity
From the ITGS Guide:
Integrity refers to the correspondence of data with itself, at its creation. Data lacks integrity when it has been changed accidentally or tampered with. For example, a hacker might change driver license data resulting in arrests of innocent people.Data integrity is concerned with the ‘correctness’ of the data. Data cannot be regarded as having integrity if it has been accidentally changed or tampered with.
Data that lacks integrity cannot be trusted but is hard to spot. Errors may be introduced into data in a variety of ways. They can be introduced when the person typing in the data misreads it off a source document or if a program or machine errors corrupt data. Some types of corruption can be caused by simple typing errors.
Validation and verification checks are performed on data to ensure its integrity.
Verification
When keying-in very large quantities of data it is normal for some errors to occur in copying from the hand-written source documents. Mistakes made when copying are known as transcription errors. It is also quite common for people to transpose characters, so that 69 would become 96, for example. To eliminate copying errors the data is re-typed by a second key-to-disk operator and any differences in the two sets of data are notified by the computer. Checking and correcting errors made when keying-in data from source documents onto disk or tape is known as verification.Validation
Validation checks are intended to ensure that the data is suitable for the purpose for which it is being used, in particular that the data is:- Of the correct type (alphabetic, numeric etc.)
- Within an acceptable numerical range
- Complete
- In the right format
Validation checks must be combined with verification checks to reduce the number of errors in data input and ensure the integrity (accuracy and completeness) of the data.Validation type checks examples:
- 6-digit STD code: acceptable 028373
rejected 0392Z5 (alphabetic character included)- car registration: acceptable ACE 3641
rejected 8CE 3641 (number instead of letter at the start)Validation range checks examples:
Tasks:
- Find a news item about data integrity or a data error problem. Briefly describe the scenario and discuss possible solutions.
- Find the 1998 Data Protection Act. What duties does it impose on those who hold personal data? Save a copy of the main principles of the act for your notes.
*AT&T hack exposes 19,000 identities
Resources
Baase, Sara. A Gift of Fire. pg.136-142Beekman, George. Computer Confluence seventh edition. Chapter 7: Database Applications and Privacy Implications
Data Protection Act 1998 by Cannelle Cuvelier
The 8 Data Protection Principles (DPA): The aim, and the 8 Data Protection Principles- Omar